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Diagnosis of Bacterial Pathogens in the Urine of Urinary-Tract-Infection Patients Using Surface-Enhanced Raman Spectroscopy

(1) Background: surface-enhanced Raman spectroscopy (SERS) is a novel method for bacteria identification. However, reported applications of SERS in clinical diagnosis are limited. In this study, we used cylindrical SERS chips to detect urine pathogens in urinary tract infection (UTI) patients. (2) M...

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Autores principales: Tien, Ni, Lin, Tzu-Hsien, Hung, Zen-Chao, Lin, Hsiu-Shen, Wang, I-Kuan, Chen, Hung-Chih, Chang, Chiz-Tzung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6321215/
https://www.ncbi.nlm.nih.gov/pubmed/30572659
http://dx.doi.org/10.3390/molecules23123374
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author Tien, Ni
Lin, Tzu-Hsien
Hung, Zen-Chao
Lin, Hsiu-Shen
Wang, I-Kuan
Chen, Hung-Chih
Chang, Chiz-Tzung
author_facet Tien, Ni
Lin, Tzu-Hsien
Hung, Zen-Chao
Lin, Hsiu-Shen
Wang, I-Kuan
Chen, Hung-Chih
Chang, Chiz-Tzung
author_sort Tien, Ni
collection PubMed
description (1) Background: surface-enhanced Raman spectroscopy (SERS) is a novel method for bacteria identification. However, reported applications of SERS in clinical diagnosis are limited. In this study, we used cylindrical SERS chips to detect urine pathogens in urinary tract infection (UTI) patients. (2) Methods: Urine samples were retrieved from 108 UTI patients. A 10 mL urine sample was sent to conventional bacterial culture as a reference. Another 10 mL urine sample was loaded on a SERS chip for bacteria identification and antibiotic susceptibility. We concentrated the urine specimen if the intensity of the Raman spectrum required enhancement. The resulting Raman spectrum was analyzed by a recognition software to compare with spectrum-form reference bacteria and was further confirmed by principal component analysis (PCA). (3) Results: There were 97 samples with single bacteria species identified by conventional urine culture and, among them, 93 can be successfully identified by using SERS without sample concentration. There were four samples that needed concentration for bacteria identification. Antibiotic susceptibility can also be found by SERS. There were seven mixed flora infections found by conventional culture, which can only be identified by the PCA method. (4) Conclusions: SERS can be used in the diagnosis of urinary tract infection with the aid of the recognition software and PCA.
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spelling pubmed-63212152019-01-14 Diagnosis of Bacterial Pathogens in the Urine of Urinary-Tract-Infection Patients Using Surface-Enhanced Raman Spectroscopy Tien, Ni Lin, Tzu-Hsien Hung, Zen-Chao Lin, Hsiu-Shen Wang, I-Kuan Chen, Hung-Chih Chang, Chiz-Tzung Molecules Article (1) Background: surface-enhanced Raman spectroscopy (SERS) is a novel method for bacteria identification. However, reported applications of SERS in clinical diagnosis are limited. In this study, we used cylindrical SERS chips to detect urine pathogens in urinary tract infection (UTI) patients. (2) Methods: Urine samples were retrieved from 108 UTI patients. A 10 mL urine sample was sent to conventional bacterial culture as a reference. Another 10 mL urine sample was loaded on a SERS chip for bacteria identification and antibiotic susceptibility. We concentrated the urine specimen if the intensity of the Raman spectrum required enhancement. The resulting Raman spectrum was analyzed by a recognition software to compare with spectrum-form reference bacteria and was further confirmed by principal component analysis (PCA). (3) Results: There were 97 samples with single bacteria species identified by conventional urine culture and, among them, 93 can be successfully identified by using SERS without sample concentration. There were four samples that needed concentration for bacteria identification. Antibiotic susceptibility can also be found by SERS. There were seven mixed flora infections found by conventional culture, which can only be identified by the PCA method. (4) Conclusions: SERS can be used in the diagnosis of urinary tract infection with the aid of the recognition software and PCA. MDPI 2018-12-19 /pmc/articles/PMC6321215/ /pubmed/30572659 http://dx.doi.org/10.3390/molecules23123374 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Tien, Ni
Lin, Tzu-Hsien
Hung, Zen-Chao
Lin, Hsiu-Shen
Wang, I-Kuan
Chen, Hung-Chih
Chang, Chiz-Tzung
Diagnosis of Bacterial Pathogens in the Urine of Urinary-Tract-Infection Patients Using Surface-Enhanced Raman Spectroscopy
title Diagnosis of Bacterial Pathogens in the Urine of Urinary-Tract-Infection Patients Using Surface-Enhanced Raman Spectroscopy
title_full Diagnosis of Bacterial Pathogens in the Urine of Urinary-Tract-Infection Patients Using Surface-Enhanced Raman Spectroscopy
title_fullStr Diagnosis of Bacterial Pathogens in the Urine of Urinary-Tract-Infection Patients Using Surface-Enhanced Raman Spectroscopy
title_full_unstemmed Diagnosis of Bacterial Pathogens in the Urine of Urinary-Tract-Infection Patients Using Surface-Enhanced Raman Spectroscopy
title_short Diagnosis of Bacterial Pathogens in the Urine of Urinary-Tract-Infection Patients Using Surface-Enhanced Raman Spectroscopy
title_sort diagnosis of bacterial pathogens in the urine of urinary-tract-infection patients using surface-enhanced raman spectroscopy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6321215/
https://www.ncbi.nlm.nih.gov/pubmed/30572659
http://dx.doi.org/10.3390/molecules23123374
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